{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "#基于matplotlib的python可视化库\n",
    "\n",
    "from matplotlib import pyplot as plt\n",
    "%matplotlib inline\n",
    "#魔法函数,不需要plt.show()图像也会显示\n",
    "\n",
    "plt.rcParams['font.sans-serif']=['SimHei']\n",
    "#图形中的中文正常编码显示\n",
    "plt.rcParams['axes.unicode_minus']=False\n",
    "#坐标轴刻度表正常显示正负号\n",
    "\n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 27598 entries, 0 to 27597\n",
      "Data columns (total 7 columns):\n",
      " #   Column         Non-Null Count  Dtype  \n",
      "---  ------         --------------  -----  \n",
      " 0   update_time    27598 non-null  object \n",
      " 1   id             27598 non-null  object \n",
      " 2   title          27598 non-null  object \n",
      " 3   price          27598 non-null  float64\n",
      " 4   sale_count     25244 non-null  float64\n",
      " 5   comment_count  25244 non-null  float64\n",
      " 6   店名             27598 non-null  object \n",
      "dtypes: float64(3), object(4)\n",
      "memory usage: 1.5+ MB\n"
     ]
    }
   ],
   "source": [
    "df=pd.read_csv('C:/Users/Auror/Desktop/双十一淘宝美妆数据.csv')\n",
    "df.info()\n",
    "#显示摘要"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>update_time</th>\n",
       "      <th>id</th>\n",
       "      <th>title</th>\n",
       "      <th>price</th>\n",
       "      <th>sale_count</th>\n",
       "      <th>comment_count</th>\n",
       "      <th>店名</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2016/11/14</td>\n",
       "      <td>A18164178225</td>\n",
       "      <td>CHANDO/自然堂 雪域精粹纯粹滋润霜50g 补水保湿 滋润水润面霜</td>\n",
       "      <td>139.0</td>\n",
       "      <td>26719.0</td>\n",
       "      <td>2704.0</td>\n",
       "      <td>自然堂</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2016/11/14</td>\n",
       "      <td>A18177105952</td>\n",
       "      <td>CHANDO/自然堂凝时鲜颜肌活乳液120ML 淡化细纹补水滋润专柜正品</td>\n",
       "      <td>194.0</td>\n",
       "      <td>8122.0</td>\n",
       "      <td>1492.0</td>\n",
       "      <td>自然堂</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2016/11/14</td>\n",
       "      <td>A18177226992</td>\n",
       "      <td>CHANDO/自然堂活泉保湿修护精华水（滋润型135ml 补水控油爽肤水</td>\n",
       "      <td>99.0</td>\n",
       "      <td>12668.0</td>\n",
       "      <td>589.0</td>\n",
       "      <td>自然堂</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2016/11/14</td>\n",
       "      <td>A18178033846</td>\n",
       "      <td>CHANDO/自然堂 男士劲爽控油洁面膏 100g 深层清洁  男士洗面奶</td>\n",
       "      <td>38.0</td>\n",
       "      <td>25805.0</td>\n",
       "      <td>4287.0</td>\n",
       "      <td>自然堂</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2016/11/14</td>\n",
       "      <td>A18178045259</td>\n",
       "      <td>CHANDO/自然堂雪域精粹纯粹滋润霜（清爽型）50g补水保湿滋润霜</td>\n",
       "      <td>139.0</td>\n",
       "      <td>5196.0</td>\n",
       "      <td>618.0</td>\n",
       "      <td>自然堂</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  update_time            id                                  title  price  \\\n",
       "0  2016/11/14  A18164178225    CHANDO/自然堂 雪域精粹纯粹滋润霜50g 补水保湿 滋润水润面霜  139.0   \n",
       "1  2016/11/14  A18177105952   CHANDO/自然堂凝时鲜颜肌活乳液120ML 淡化细纹补水滋润专柜正品  194.0   \n",
       "2  2016/11/14  A18177226992   CHANDO/自然堂活泉保湿修护精华水（滋润型135ml 补水控油爽肤水   99.0   \n",
       "3  2016/11/14  A18178033846  CHANDO/自然堂 男士劲爽控油洁面膏 100g 深层清洁  男士洗面奶   38.0   \n",
       "4  2016/11/14  A18178045259     CHANDO/自然堂雪域精粹纯粹滋润霜（清爽型）50g补水保湿滋润霜  139.0   \n",
       "\n",
       "   sale_count  comment_count   店名  \n",
       "0     26719.0         2704.0  自然堂  \n",
       "1      8122.0         1492.0  自然堂  \n",
       "2     12668.0          589.0  自然堂  \n",
       "3     25805.0         4287.0  自然堂  \n",
       "4      5196.0          618.0  自然堂  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()\n",
    "#显示前5行"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.duplicated().sum()#计算重复条数\n",
    "df.drop_duplicates(inplace=True)#去除重复值\n",
    "df.shape#查看去重后数据条数\n",
    "df.reset_index(inplace=True,drop=True)#重置索引 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "update_time      False\n",
       "id               False\n",
       "title            False\n",
       "price            False\n",
       "sale_count        True\n",
       "comment_count     True\n",
       "店名               False\n",
       "dtype: bool"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().any()#查看存在哪些缺失值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
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       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>price</th>\n",
       "      <th>sale_count</th>\n",
       "      <th>comment_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>27512.000000</td>\n",
       "      <td>2.516200e+04</td>\n",
       "      <td>25162.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>363.423512</td>\n",
       "      <td>1.231605e+04</td>\n",
       "      <td>1121.741197</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>614.876153</td>\n",
       "      <td>5.241236e+04</td>\n",
       "      <td>5277.781581</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>99.000000</td>\n",
       "      <td>2.780000e+02</td>\n",
       "      <td>21.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>205.000000</td>\n",
       "      <td>1.443000e+03</td>\n",
       "      <td>153.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>390.000000</td>\n",
       "      <td>6.353000e+03</td>\n",
       "      <td>669.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>11100.000000</td>\n",
       "      <td>1.923160e+06</td>\n",
       "      <td>202930.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              price    sale_count  comment_count\n",
       "count  27512.000000  2.516200e+04   25162.000000\n",
       "mean     363.423512  1.231605e+04    1121.741197\n",
       "std      614.876153  5.241236e+04    5277.781581\n",
       "min        1.000000  0.000000e+00       0.000000\n",
       "25%       99.000000  2.780000e+02      21.000000\n",
       "50%      205.000000  1.443000e+03     153.000000\n",
       "75%      390.000000  6.353000e+03     669.000000\n",
       "max    11100.000000  1.923160e+06  202930.000000"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()#描述统计"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    0.0\n",
       "dtype: float64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sale_count.mode()#sale_count的众数\n",
    "df.comment_count.mode()#comment_count的众数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "#sale_count,comment_count的众数都为0，用0填补空值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "update_time      0\n",
       "id               0\n",
       "title            0\n",
       "price            0\n",
       "sale_count       0\n",
       "comment_count    0\n",
       "店名               0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.fillna(0,inplace=True)\n",
    "df.sale_count=df.sale_count.astype('int64')\n",
    "#强制转换类型为整型\n",
    "df.isnull().sum()#检查是否完成缺失值的处理"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Building prefix dict from the default dictionary ...\n",
      "Loading model from cache C:\\Users\\Auror\\AppData\\Local\\Temp\\jieba.cache\n",
      "Loading model cost 0.609 seconds.\n",
      "Prefix dict has been built successfully.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>title</th>\n",
       "      <th>name_cut</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>CHANDO/自然堂 雪域精粹纯粹滋润霜50g 补水保湿 滋润水润面霜</td>\n",
       "      <td>[CHANDO, /, 自然, 堂,  , 雪域, 精粹, 纯粹, 滋润霜, 50g,  ,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>CHANDO/自然堂凝时鲜颜肌活乳液120ML 淡化细纹补水滋润专柜正品</td>\n",
       "      <td>[CHANDO, /, 自然, 堂, 凝, 时鲜, 颜肌活, 乳液, 120ML,  , 淡...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>CHANDO/自然堂活泉保湿修护精华水（滋润型135ml 补水控油爽肤水</td>\n",
       "      <td>[CHANDO, /, 自然, 堂, 活泉, 保湿, 修护, 精华, 水, （, 滋润, 型...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>CHANDO/自然堂 男士劲爽控油洁面膏 100g 深层清洁  男士洗面奶</td>\n",
       "      <td>[CHANDO, /, 自然, 堂,  , 男士, 劲爽, 控油, 洁面膏,  , 100g...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>CHANDO/自然堂雪域精粹纯粹滋润霜（清爽型）50g补水保湿滋润霜</td>\n",
       "      <td>[CHANDO, /, 自然, 堂, 雪域, 精粹, 纯粹, 滋润霜, （, 清爽型, ）,...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                   title  \\\n",
       "0    CHANDO/自然堂 雪域精粹纯粹滋润霜50g 补水保湿 滋润水润面霜   \n",
       "1   CHANDO/自然堂凝时鲜颜肌活乳液120ML 淡化细纹补水滋润专柜正品   \n",
       "2   CHANDO/自然堂活泉保湿修护精华水（滋润型135ml 补水控油爽肤水   \n",
       "3  CHANDO/自然堂 男士劲爽控油洁面膏 100g 深层清洁  男士洗面奶   \n",
       "4     CHANDO/自然堂雪域精粹纯粹滋润霜（清爽型）50g补水保湿滋润霜   \n",
       "\n",
       "                                            name_cut  \n",
       "0  [CHANDO, /, 自然, 堂,  , 雪域, 精粹, 纯粹, 滋润霜, 50g,  ,...  \n",
       "1  [CHANDO, /, 自然, 堂, 凝, 时鲜, 颜肌活, 乳液, 120ML,  , 淡...  \n",
       "2  [CHANDO, /, 自然, 堂, 活泉, 保湿, 修护, 精华, 水, （, 滋润, 型...  \n",
       "3  [CHANDO, /, 自然, 堂,  , 男士, 劲爽, 控油, 洁面膏,  , 100g...  \n",
       "4  [CHANDO, /, 自然, 堂, 雪域, 精粹, 纯粹, 滋润霜, （, 清爽型, ）,...  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import jieba\n",
    "#jieba-中文分词库\n",
    "title_cut=[]\n",
    "for i in df.title:\n",
    "    j=jieba.lcut(i)\n",
    "    title_cut.append(j)\n",
    "df['name_cut']=title_cut\n",
    "df[['title','name_cut']].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'乳液': ('护肤品', '乳液类'),\n",
       " '美白乳': ('护肤品', '乳液类'),\n",
       " '润肤乳 凝乳': ('护肤品', '乳液类'),\n",
       " \"柔肤液'\": ('护肤品', '乳液类'),\n",
       " '亮肤乳': ('护肤品', '乳液类'),\n",
       " '菁华乳': ('护肤品', '乳液类'),\n",
       " '眼霜': ('护肤品', '眼部护理'),\n",
       " '眼部精华': ('护肤品', '眼部护理'),\n",
       " '洗面': ('护肤品', '清洁类'),\n",
       " '洁面': ('护肤品', '清洁类'),\n",
       " '清洁': ('护肤品', '清洁类'),\n",
       " '卸妆': ('护肤品', '清洁类'),\n",
       " '洁颜': ('护肤品', '清洁类'),\n",
       " '洗颜': ('护肤品', '清洁类'),\n",
       " '去角质': ('护肤品', '清洁类'),\n",
       " '化妆水': ('护肤品', '化妆水'),\n",
       " '爽肤水': ('护肤品', '化妆水'),\n",
       " '柔肤水': ('护肤品', '化妆水'),\n",
       " '补水露': ('护肤品', '化妆水'),\n",
       " '凝露': ('护肤品', '化妆水'),\n",
       " '柔肤液': ('护肤品', '化妆水'),\n",
       " '精粹水': ('护肤品', '化妆水'),\n",
       " '亮肤水': ('护肤品', '化妆水'),\n",
       " '润肤水': ('护肤品', '化妆水'),\n",
       " '保湿水': ('护肤品', '化妆水'),\n",
       " '菁华水': ('护肤品', '化妆水'),\n",
       " '保湿喷雾': ('护肤品', '化妆水'),\n",
       " '面霜': ('护肤品', '面霜类'),\n",
       " '日霜': ('护肤品', '面霜类'),\n",
       " '晚霜': ('护肤品', '面霜类'),\n",
       " '柔肤霜': ('护肤品', '面霜类'),\n",
       " '滋润霜': ('护肤品', '面霜类'),\n",
       " '保湿霜': ('护肤品', '面霜类'),\n",
       " '凝霜': ('护肤品', '面霜类'),\n",
       " '日间霜': ('护肤品', '面霜类'),\n",
       " '晚间霜': ('护肤品', '面霜类'),\n",
       " '乳霜': ('护肤品', '面霜类'),\n",
       " '修护霜': ('护肤品', '面霜类'),\n",
       " '亮肤霜': ('护肤品', '面霜类'),\n",
       " '底霜': ('护肤品', '面霜类'),\n",
       " '精华液': ('护肤品', '精华类'),\n",
       " '精华水': ('护肤品', '精华类'),\n",
       " '精华露': ('护肤品', '精华类'),\n",
       " '防晒霜': ('护肤品', '防晒类'),\n",
       " '唇釉': ('化妆品', '口红类'),\n",
       " '口红': ('化妆品', '口红类'),\n",
       " '散粉': ('化妆品', '底妆类'),\n",
       " '蜜粉': ('化妆品', '底妆类'),\n",
       " '粉底液': ('化妆品', '底妆类'),\n",
       " '定妆粉 ': ('化妆品', '底妆类'),\n",
       " '气垫': ('化妆品', '底妆类'),\n",
       " '粉饼': ('化妆品', '底妆类'),\n",
       " 'BB': ('化妆品', '底妆类'),\n",
       " 'CC': ('化妆品', '底妆类'),\n",
       " '遮瑕': ('化妆品', '底妆类'),\n",
       " '粉霜': ('化妆品', '底妆类'),\n",
       " '粉底膏': ('化妆品', '底妆类'),\n",
       " '眉粉': ('化妆品', '眼部彩妆'),\n",
       " '染眉膏': ('化妆品', '眼部彩妆'),\n",
       " '眼线': ('化妆品', '眼部彩妆'),\n",
       " '眼影': ('化妆品', '眼部彩妆'),\n",
       " '鼻影': ('化妆品', '修容类'),\n",
       " '修容粉': ('化妆品', '修容类'),\n",
       " '高光': ('化妆品', '修容类')}"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "first_type=[]#主类别\n",
    "second_type=[]#子类别\n",
    "basic_config_data = '''护肤品\t套装\t套装\t\t\t\t\t\t\t\n",
    "护肤品\t乳液类\t乳液\t美白乳\t润肤乳 凝乳\t柔肤液'\t亮肤乳\t菁华乳\t修护乳\n",
    "护肤品\t眼部护理\t眼霜\t眼部精华\t眼膜\t\t\t\t\t\n",
    "护肤品\t面膜类\t面膜\t\t\t\t\t\t\t\t\t\t\t\t\t\n",
    "护肤品\t清洁类\t洗面\t洁面\t清洁\t卸妆\t洁颜\t洗颜\t去角质\t磨砂\t\t\t\t\t\t\n",
    "护肤品\t化妆水\t化妆水\t爽肤水\t柔肤水\t补水露\t凝露\t柔肤液\t精粹水\t亮肤水\t润肤水\t保湿水\t菁华水\t保湿喷雾\t舒缓喷雾\n",
    "护肤品\t面霜类\t面霜\t日霜\t晚霜\t柔肤霜\t滋润霜\t保湿霜\t凝霜\t日间霜\t晚间霜\t乳霜\t修护霜\t亮肤霜\t底霜\t菁华霜\n",
    "护肤品\t精华类\t精华液\t精华水\t精华露\t精华素\t\t\t\t\t\t\t\t\t\t\n",
    "护肤品\t防晒类\t防晒霜\t防晒喷雾\t\t\t\t\t\t\t\t\t\t\t\t\n",
    "化妆品\t口红类\t唇釉\t口红\t唇彩\t\t\t\t\t\t\t\t\t\t\t\n",
    "化妆品\t底妆类\t散粉\t蜜粉\t粉底液\t定妆粉 \t气垫\t粉饼\tBB\tCC\t遮瑕\t粉霜\t粉底膏\t粉底霜\t\t\n",
    "化妆品\t眼部彩妆\t眉粉\t染眉膏\t眼线\t眼影\t睫毛膏\t\t\t\t\t\t\t\t\t\n",
    "化妆品\t修容类\t鼻影\t修容粉\t高光\t腮红\t\t\t\t\t\t\t\t\t\t\n",
    "其他\t其他\t其他'''#标准分类\n",
    "category_map={}\n",
    "for m in basic_config_data.split('\\n'):\n",
    "    basic_category_list=m.strip().strip('\\n').strip('\\t').split('\\t')\n",
    "    first_category=basic_category_list[0]\n",
    "    second_category=basic_category_list[1]\n",
    "    unit_category_list=basic_category_list[2:-1]\n",
    "    for unit_category in unit_category_list:\n",
    "        if unit_category and unit_category.strip().strip('\\t'):\n",
    "            category_map[unit_category]=(first_category,second_category)\n",
    "category_map\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in range(len(df)):\n",
    "    exist=False\n",
    "    for j in df['name_cut'][i]:\n",
    "        if j in category_map:\n",
    "            first_type.append(category_map.get(j)[0])\n",
    "            second_type.append(category_map.get(j)[1])\n",
    "            exist=True\n",
    "            break\n",
    "    if not exist:\n",
    "        first_type.append('其他')\n",
    "        second_type.append('其他')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "27512 27512 27512\n"
     ]
    }
   ],
   "source": [
    "print(len(df),len(first_type),len(second_type))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['first_type']=first_type\n",
    "df['second_type']=second_type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "其他     13210\n",
       "护肤品    11129\n",
       "化妆品     3173\n",
       "Name: first_type, dtype: int64"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.first_type.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "其他      13210\n",
       "清洁类      2922\n",
       "面霜类      2685\n",
       "化妆水      1955\n",
       "底妆类      1790\n",
       "乳液类      1232\n",
       "眼部护理     1114\n",
       "精华类       727\n",
       "口红类       715\n",
       "眼部彩妆      604\n",
       "防晒类       494\n",
       "修容类        64\n",
       "Name: second_type, dtype: int64"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.second_type.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "gender=[]\n",
    "for i in range(len(df)):\n",
    "    if '男' in df.name_cut[i]:\n",
    "        gender.append('是')\n",
    "    elif '男生' in df.name_cut[i]:\n",
    "        gender.append('是')\n",
    "    elif '男士' in df.name_cut[i]:\n",
    "        gender.append('是')\n",
    "    else:\n",
    "        gender.append('否')\n",
    "        \n",
    "df['gender']=gender"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>title</th>\n",
       "      <th>price</th>\n",
       "      <th>sale_count</th>\n",
       "      <th>comment_count</th>\n",
       "      <th>店名</th>\n",
       "      <th>first_type</th>\n",
       "      <th>second_type</th>\n",
       "      <th>gender</th>\n",
       "      <th>销售额</th>\n",
       "      <th>日期</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>update_time</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2016-11-14</th>\n",
       "      <td>A18164178225</td>\n",
       "      <td>CHANDO/自然堂 雪域精粹纯粹滋润霜50g 补水保湿 滋润水润面霜</td>\n",
       "      <td>139.0</td>\n",
       "      <td>26719</td>\n",
       "      <td>2704.0</td>\n",
       "      <td>自然堂</td>\n",
       "      <td>护肤品</td>\n",
       "      <td>面霜类</td>\n",
       "      <td>否</td>\n",
       "      <td>3713941.0</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-11-14</th>\n",
       "      <td>A18177105952</td>\n",
       "      <td>CHANDO/自然堂凝时鲜颜肌活乳液120ML 淡化细纹补水滋润专柜正品</td>\n",
       "      <td>194.0</td>\n",
       "      <td>8122</td>\n",
       "      <td>1492.0</td>\n",
       "      <td>自然堂</td>\n",
       "      <td>护肤品</td>\n",
       "      <td>乳液类</td>\n",
       "      <td>否</td>\n",
       "      <td>1575668.0</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-11-14</th>\n",
       "      <td>A18177226992</td>\n",
       "      <td>CHANDO/自然堂活泉保湿修护精华水（滋润型135ml 补水控油爽肤水</td>\n",
       "      <td>99.0</td>\n",
       "      <td>12668</td>\n",
       "      <td>589.0</td>\n",
       "      <td>自然堂</td>\n",
       "      <td>护肤品</td>\n",
       "      <td>化妆水</td>\n",
       "      <td>否</td>\n",
       "      <td>1254132.0</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-11-14</th>\n",
       "      <td>A18178033846</td>\n",
       "      <td>CHANDO/自然堂 男士劲爽控油洁面膏 100g 深层清洁  男士洗面奶</td>\n",
       "      <td>38.0</td>\n",
       "      <td>25805</td>\n",
       "      <td>4287.0</td>\n",
       "      <td>自然堂</td>\n",
       "      <td>护肤品</td>\n",
       "      <td>清洁类</td>\n",
       "      <td>是</td>\n",
       "      <td>980590.0</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-11-14</th>\n",
       "      <td>A18178045259</td>\n",
       "      <td>CHANDO/自然堂雪域精粹纯粹滋润霜（清爽型）50g补水保湿滋润霜</td>\n",
       "      <td>139.0</td>\n",
       "      <td>5196</td>\n",
       "      <td>618.0</td>\n",
       "      <td>自然堂</td>\n",
       "      <td>护肤品</td>\n",
       "      <td>面霜类</td>\n",
       "      <td>否</td>\n",
       "      <td>722244.0</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       id                                  title  price  \\\n",
       "update_time                                                               \n",
       "2016-11-14   A18164178225    CHANDO/自然堂 雪域精粹纯粹滋润霜50g 补水保湿 滋润水润面霜  139.0   \n",
       "2016-11-14   A18177105952   CHANDO/自然堂凝时鲜颜肌活乳液120ML 淡化细纹补水滋润专柜正品  194.0   \n",
       "2016-11-14   A18177226992   CHANDO/自然堂活泉保湿修护精华水（滋润型135ml 补水控油爽肤水   99.0   \n",
       "2016-11-14   A18178033846  CHANDO/自然堂 男士劲爽控油洁面膏 100g 深层清洁  男士洗面奶   38.0   \n",
       "2016-11-14   A18178045259     CHANDO/自然堂雪域精粹纯粹滋润霜（清爽型）50g补水保湿滋润霜  139.0   \n",
       "\n",
       "             sale_count  comment_count   店名 first_type second_type gender  \\\n",
       "update_time                                                                 \n",
       "2016-11-14        26719         2704.0  自然堂        护肤品         面霜类      否   \n",
       "2016-11-14         8122         1492.0  自然堂        护肤品         乳液类      否   \n",
       "2016-11-14        12668          589.0  自然堂        护肤品         化妆水      否   \n",
       "2016-11-14        25805         4287.0  自然堂        护肤品         清洁类      是   \n",
       "2016-11-14         5196          618.0  自然堂        护肤品         面霜类      否   \n",
       "\n",
       "                   销售额  日期  \n",
       "update_time                 \n",
       "2016-11-14   3713941.0  14  \n",
       "2016-11-14   1575668.0  14  \n",
       "2016-11-14   1254132.0  14  \n",
       "2016-11-14    980590.0  14  \n",
       "2016-11-14    722244.0  14  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['销售额']=df.sale_count*df.price\n",
    "df['update_time']=pd.to_datetime(df['update_time'])\n",
    "df=df.set_index('update_time')\n",
    "df['日期']=df.index.day\n",
    "del df['name_cut']\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "DatetimeIndex: 27512 entries, 2016-11-14 to 2016-11-05\n",
      "Data columns (total 11 columns):\n",
      " #   Column         Non-Null Count  Dtype  \n",
      "---  ------         --------------  -----  \n",
      " 0   id             27512 non-null  object \n",
      " 1   title          27512 non-null  object \n",
      " 2   price          27512 non-null  float64\n",
      " 3   sale_count     27512 non-null  int64  \n",
      " 4   comment_count  27512 non-null  float64\n",
      " 5   店名             27512 non-null  object \n",
      " 6   first_type     27512 non-null  object \n",
      " 7   second_type    27512 non-null  object \n",
      " 8   gender         27512 non-null  object \n",
      " 9   销售额            27512 non-null  float64\n",
      " 10  日期             27512 non-null  int64  \n",
      "dtypes: float64(3), int64(2), object(6)\n",
      "memory usage: 2.5+ MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "#保存清理好的数据为Excel格式\n",
    "df.to_excel('clean_beautymakeup.xls',sheet_name='clean_data')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['id', 'title', 'price', 'sale_count', 'comment_count', '店名',\n",
       "       'first_type', 'second_type', 'gender', '销售额', '日期'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "悦诗风吟    3021\n",
       "佰草集     2264\n",
       "欧莱雅     1942\n",
       "雅诗兰黛    1810\n",
       "倩碧      1703\n",
       "美加净     1678\n",
       "欧珀莱     1359\n",
       "相宜本草    1313\n",
       "妮维雅     1299\n",
       "兰蔻      1285\n",
       "娇兰      1193\n",
       "自然堂     1175\n",
       "玉兰油     1131\n",
       "兰芝      1088\n",
       "美宝莲      825\n",
       "资生堂      821\n",
       "植村秀      750\n",
       "薇姿       746\n",
       "雅漾       663\n",
       "雪花秀      543\n",
       "SKII     469\n",
       "蜜丝佛陀     434\n",
       "Name: 店名, dtype: int64"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['店名'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,axes=plt.subplots(1,2,figsize=(12,10))\n",
    "\n",
    "ax1=df.groupby(['店名']).sale_count.sum().sort_values(ascending=True).plot(kind='barh',ax=axes[0],width=0.6)\n",
    "ax1.set_xlabel('总销量',fontsize=12)\n",
    "ax1.set_ylabel('品牌',fontsize=12)\n",
    "ax1.set_title('各品牌总销量对比',fontsize=14)\n",
    "\n",
    "ax2=df['销售额'].groupby(df.店名).sum().sort_values(ascending=True).plot(kind='barh',ax=axes[1],width=0.6)\n",
    "ax2.set_xlabel('总销售额',fontsize=12)\n",
    "ax2.set_ylabel('品牌',fontsize=12)\n",
    "ax2.set_title('各品牌总销售额对比',fontsize=14)\n",
    "\n",
    "plt.subplots_adjust(wspace=0.4)\n",
    "plt.savefig('./各品牌总销量和销售额对比.png')\n",
    "\n",
    "plt.show()\n",
    "\n",
    "#对比分析各品牌的总销量和总销售额"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1280x640 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#品牌热度\n",
    "a=df['comment_count'].groupby(df['店名']).sum().sort_values(ascending=False)\n",
    "plt.figure(figsize=(16,8),dpi=80)\n",
    "b=list(range(len(a)))\n",
    "plt.bar(b,a.values,width=0.4,color='#0c84c6')\n",
    "plt.xticks(b,a.index,fontsize=12,rotation=90)\n",
    "plt.xlabel('品牌',fontsize=12)\n",
    "plt.ylabel('评论热度',fontsize=12)\n",
    "plt.title('各品牌双十一期间的评论热度',fontsize=14)\n",
    "plt.savefig('./各品牌双十一期间的评论热度.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "#根据上图分析得,评论热度较高的是:悦诗风吟、妮维雅、美宝莲、相宜本草、自然堂"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 960x480 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,6),dpi=80)\n",
    "plt.grid(linestyle='-.',color='gray',axis='x',alpha=0.5)\n",
    "b1=df['sale_count'].groupby(df['日期']).sum()\n",
    "b2=df['comment_count'].groupby(df['日期']).sum()\n",
    "x=b1.index\n",
    "ax1=plt.subplot(111)\n",
    "ax1.plot(x,b1.values,label='销量')\n",
    "ax1.legend(loc='upper left')\n",
    "ax1.set_ylabel('销量',fontsize=12)\n",
    "ax2=ax1.twinx()\n",
    "ax2.plot(x,b2.values,label='评论热度',color='r')\n",
    "ax2.legend(loc='upper right')\n",
    "ax2.set_ylabel('评论热度',fontsize=12)\n",
    "\n",
    "ax1.set_xlabel('日期(11月)',fontsize=12)\n",
    "ax2.set_xticks(list(range(5,15)))\n",
    "plt.savefig('./销量,热度随时间的变化分析')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#从上图来看,在淘宝双十一购物节中,美妆类产品的销量与评论的相关性极高"
   ]
  }
 ],
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